"""
Unfortunately, there weren’t enough lifeboats for everyone onboard,
resulting in the death of 1502 out of 2224 passengers and crew.

While there was some element of luck involved in surviving,
it seems some groups of people were more likely to survive than others.

In this challenge,
we ask you to build a predictive model that answers the question:
“what sorts of people were more likely to survive?”
using passenger data (ie name, age, gender, socio-economic class, etc).
"""

import pandas as pd

ttn_train_data = pd.read_csv('datasets/train.csv')

print(ttn_train_data.describe())

print(ttn_train_data.head())

print(ttn_train_data.columns)

y = ttn_train_data['Survived']

features = ['Pclass', 'Age']

X = ttn_train_data[features]
print(X.describe())
print(X.head())

# 二分类处理
